Get the latest tech news

Microsoft’s new rStar-Math technique upgrades small models to outperform OpenAI’s o1-preview at math problems

Phi-4 and an rStar-Math paper suggest that compact, specialized models can provide powerful alternatives to the industry’s largest systems.

It showed improved performance on all of them, even exceeding OpenAI’s previously most advanced model at the MATH(word problem solving) third-party benchmark of 12,500 questions covering various branches such as geometry and algebra, and all levels of difficulty. While the Phi-4 release has expanded access to high-performance small models, rStar-Math showcases a specialized approach: using smaller AI systems to achieve state-of-the-art results in mathematical reasoning. The key to rStar-Math is that it leverages Monte Carlo Tree Search (MCTS), a method that mimics human “deep thinking” by iteratively refining step-by-step solutions to mathematical problems.

Get the Android app